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    <title>Python3数据科学入门与实战</title>
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        <h3>
            第1章 实验环境的搭建
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                    1-1 导学视频 (08:36) </a>


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                    1-2 Anaconda和Jupyter notebook介绍 (12:11) </a>


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                    1-3 Anaconda在Mac上的安装演示 (06:57) </a>


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                    1-4 Anaconda在windows上安装演示 (05:09) </a>


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                    1-5 Anaconda在Linux上的安装演示 (09:52) </a>


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                    1-6 Jupyter-notebook的使用演示 (08:43) </a>


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            第2章 Numpy入门
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                    2-1 数据科学领域5个常用Python库 (06:08) </a>


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                    2-2 数学基础回顾之矩阵运算 (06:07) </a>


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                    2-3 Array的创建及访问 (10:44) </a>


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                    2-4 数组与矩阵运算 (10:49) </a>


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                    2-5 Array的input和output (05:39) </a>


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            第3章 Pandas入门
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                    3-1 Pandas Series (08:32) </a>


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                    3-2 Pandas DataFrame (09:34) </a>


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                    3-3 深入理解Series和Dataframe (11:30) </a>


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                    3-4 Pandas-Dataframe-IO操作 (08:53) </a>


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                    3-5 DataFrame的Selecting和indexing (13:43) </a>


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                    3-6 Series和Dataframe的Reindexing (11:03) </a>


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                    3-7 谈一谈NaN (11:15) </a>


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                    3-8 多级Index (11:29) </a>


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                    3-9 Mapping和Replace (09:12) </a>


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            第4章 Pandas玩转数据
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                    4-1 DataFrame的简单数学计算 (08:44) </a>


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                    4-2 Series和DataFrame的排序 (09:17) </a>


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                    4-3 重命名Dataframe的index (15:22) </a>


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                    4-4 DataFrame的merge操作 (10:09) </a>


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                    4-5 Concatenate和Combine (11:58) </a>


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                    4-6 通过apply进行数据预处理 (10:33) </a>


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                    4-7 通过去重进行数据清洗 (07:18) </a>


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                    4-8 时间序列操作基础 (13:01) </a>


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                    4-9 时间序列数据的采样和画图 (14:33) </a>


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                    4-10 数据分箱技术Binning (09:22) </a>


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                    4-11 数据分组技术GroupBy (12:35) </a>


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                    4-12 数据聚合技术Aggregation (07:27) </a>


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                    4-13 透视表 (13:52) </a>


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                    4-14 分组和透视功能实战 (22:01) </a>


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                    4-15 Streaming DataFrame (09:20) </a>


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            第5章 绘图和可视化之Matplotlib
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                    5-1 Matplotlib介绍 (09:46) </a>


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                    5-2 matplotlib简单绘图之plot (15:27) </a>


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                    5-3 matplotlib简单绘图之subplot (12:59) </a>


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                    5-4 Pandas绘图之Series (09:32) </a>


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                    5-5 Pandas绘图之DataFrame (10:15) </a>


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                    5-6 直方图和密度图 (10:36) </a>


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            第6章 绘图和可视化之Seaborn
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                    6-1 seaborn介绍 (08:22) </a>


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                    6-2 seaborn实现直方图和密度图 (08:28) </a>


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                    6-3 seaborn实现柱状图和热力图 (12:52) </a>


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                    6-4 seaborn图形显示效果的设置 (15:22) </a>


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                    6-5 seaborn强大的调色功能 (16:27) </a>


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            第7章 数据分析项目实战
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                    7-1 实战准备 (05:30) </a>


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                    7-2 股票市场分析实战之数据获取 (07:01) </a>


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                    7-3 股票市场分析实战之历史趋势分析 (14:01) </a>


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                    7-4 股票市场分析实战之风险分析 (15:36) </a>


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            第8章 课程总结
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                    8-1 总结 (04:24) </a>


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        <span>本课程已完结</span>
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